There has been increasing interest in applying machine learning applications to more tasks. This increase has been fueled by an increase in the availability of inexpensive computing power, providing deep learning applications that use many layers of processing nodes at low computational cost. Conventionally, such deep learning processes require enormous computational resources, and so are absent from the everyday appliances, vehicles, and portable personal devices in the everyday world of daily living that is far removed from enterprise computers and large server facilities, and where everyday devices have only relatively limited computational resources.